" dx v(x) $ % You may also have seen this written in shorthand form as. & ' v(x) + u(x) '# % ! d

Size: px
Start display at page:

Download "" dx v(x) $ % You may also have seen this written in shorthand form as. & ' v(x) + u(x) '# % ! d"

Transcription

1 Calculus II MAT 146 Mthods of Intgration: Intgration by Parts Just as th mthod of substitution is an intgration tchniqu that rvrss th drivativ procss calld th chain rul, Intgration by parts is a mthod of intgration that rvrss anothr drivativ procss, this on calld th product rul. Th Product Rul For two functions, ux) and vx), th product rul for drivativs stats that d dx [ ux)vx) ] =! # d dx ux) $! d ' vx) + ux) '# % dx vx) $. % You may also hav sn this writtn in shorthand form as du! v) = du! v + u! dv. In words, w might say that th drivativ of th product of two functions is th drivativ of th first function tims th scond function plus th first function tims th drivativ of th scond function. Whn w bgin with th shorthand rprsntation abov, w can crat a formula for intgration by parts by intgrating ach trm in th quation: du!v) = du! v + u!dv # du!v) = # du!v + # u!dv # duv) = # vdu + # udv uv = # vdu + # udv uv $ # vdu = # udv or # udv = uv $ # vdu Intgrat ach trm of th quation. Rwrit. On th lft sid, th intgral of a drivativ givs us th original product. Subtract vdu! from both sids of th quation. Switch lft-sid and right-sid xprssions traditional rprsntation). Th last quation in th abov drivation is th intgration-by-parts formula. It stats that th intgral of a product whos factors ar a function u and th drivativ of anothr function v is quivalnt to th diffrnc btwn th product of th two functions, u and v, and th intgral of th product composd of th function v and th drivativ of th function u.

2 Exampl 1: Us intgration by parts to valuat! x x dx, whru = x and dv = x dx. To apply th intgration-by-parts formula, w nd to dtrmin du and v. Th tabl format shown blow is a usful way to organiz th information: u = x dv = x dx du = dx v = x W startd th tabl by placing th known information, u and dv, in th top row. W compltd th tabl by calculating du and v and placing thm in th appropriat columns in th scond row. Whn th tabl is complt it bcoms a hlpful dvic for complting th intgration-by-parts task. u = x dv = x dx du = dx v = x From th tabl w writ th product of u and v ) and subtract from it th intgral of th product of v and du ). From th tabl, w gt! x x dx = x x! x dx W still ar lft with an intgral xprssion on th right sid of th quation, but this is on w can valuat by inspction:! x x dx = x x! x dx = x x x + C Exampl 2: Us intgration by parts to valuat! x ln x)dx. W hav two choics for th substitutions: u = x dv = lnx)dx u = ln x) dv = xdx du = dx v =? du = 1 x dx v = 1 2 x 2 Although our choic may not hav bn immdiatly clar at th start, by looking at th two options for substitutions, only on sms promising now. 1 W procd using th information in th right-hand tabl. 1 Th antidrivativ of lnx) dos xist. Drivd in Exampl 3, it is xlnx)-x. For most of us, howvr, that antidrivativ cannot b dtrmind by inspction, and that s a goal for intgration by parts.

3 u = ln x ) dv = xdx This lads to du = 1 x dx v = 1 2 x 2! x ln x)dx = ln x) 1 2 x 2 # $ 1 ' % 2 x2 ) $ 1 % x dx '! ) = 1 2 x 2 ln x) # 1! 2 xdx = 1 2 x 2 ln x ) # 1 2 $ 1 ' % 2 x2 ) + C = 1 2 x 2 ln x) # 1 4 x2 + C Exampl 3: Us intgration by parts to valuat! lnx)dx. Dtrmin th substitutions ndd for intgration by parts: u = ln x) dv = dx 1 This lads to du = 1 x dx v = x $ 1! lnx)dx = lnx) x # x % x dx '! ) 1 = x lnx) # dx! = x lnx) # x 1 = ln) # ) # 1ln1) #1) = # ) # 0 #1) = 1 In ths xampls, w s th importanc of our choics for u and dv. Thr ar thr important guidlins to kp in mind whn making ths choics. Whn choosing u, our goal should b an xprssion that simplifis whn it is diffrntiatd. If du is not a simplr xprssion than u, rconsidr your choic.

4 Your choic for dv should b an xprssion that can b asily intgratd s Exampl 2). Th intgral! vdu should b simplr to valuat that th original intgral! udv. Th nxt xampl illustrats that it could tak mor than on application of intgration by parts to valuat an intgral. Exampl 4: Evaluat! x sin xdx. Possibl substitutions: u = x dv = sin xdx u = sin x dv = x dx du = x dx v =! cos x du = cos xdx v = x Ths ar almost idntical, xcpt for a ngativ sign. W ll procd hr using th lft-hand tabl to illustrat th importanc of sign changs! x sin xdx = x cosx +! x cos xdx Th intgral on th right sid of th quation is similar to th on w startd with. It s valu is not radily apparnt, so w apply th intgration-by-parts tchniqu to it. For! x cos xdx, lt u = x and lt dv = cosxdx. Thn du = x dx and v = sinx. This givs us! x cos xdx = x sin x! x sin xdx. Substituting th right-hand xprssion for th lft in th first intgration-by-parts application, w gt! x sin xdx = x cosx +! x cos xdx ) = x cosx + x sin x x sin xdx! = x cosx + x sin x! x sin xdx W again sm to b lft with an intgral that rquirs furthr valuation. Notic, howvr, that th intgral on th lft sid of th quation is th sam as th on on th right sid. W can simplify th quation abov to complt th valuation of th original intgral:! x sin xdx = x cos x + x sin x! x sin xdx ) = x cos x + x sin x 2 x sin xdx! )! x sin xdx = 1 2 x cos x + x sin x = 1 2 x sin x cos x) + C

5 You might try valuating th original intgral of Exampl 4 using th altrnativ tabl of substitutions drivd at th bginning of th solution. What do you find? Is this what you xpctd?

8.3 INTEGRATION BY PARTS

8.3 INTEGRATION BY PARTS 8.3 Intgration By Parts Contmporary Calculus 8.3 INTEGRATION BY PARTS Intgration by parts is an intgration mthod which nabls us to find antidrivativs of som nw functions such as ln(x) and arctan(x) as

More information

Systems in Three Variables. No solution No point lies in all three planes. One solution The planes intersect at one point.

Systems in Three Variables. No solution No point lies in all three planes. One solution The planes intersect at one point. 3-5 Systms in Thr Variabls TEKS FOCUS VOCABULARY TEKS (3)(B) Solv systms of thr linar quations in thr variabls by using Gaussian limination, tchnology with matrics, and substitution. Rprsntation a way

More information

Unit #11 : Integration by Parts, Average of a Function. Goals: Learning integration by parts. Computing the average value of a function.

Unit #11 : Integration by Parts, Average of a Function. Goals: Learning integration by parts. Computing the average value of a function. Unit #11 : Integration by Parts, Average of a Function Goals: Learning integration by parts. Computing the average value of a function. Integration Method - By Parts - 1 Integration by Parts So far in

More information

2018 How to Apply. Application Guide. BrandAdvantage

2018 How to Apply. Application Guide. BrandAdvantage 2018 How to Apply Application Guid BrandAdvantag Contnts Accssing th Grant Sit... 3 Wlcom pag... 3 Logging in To Pub Charity... 4 Rgistration for Nw Applicants ( rgistr now )... 5 Organisation Rgistration...

More information

DO NOW Geometry Regents Lomac Date. due. Similar by Transformation 6.1 J'' J''' J'''

DO NOW Geometry Regents Lomac Date. due. Similar by Transformation 6.1 J'' J''' J''' DO NOW Gomtry Rgnts Lomac 2014-2015 Dat. du. Similar by Transformation 6.1 (DN) Nam th thr rigid transformations and sktch an xampl that illustrats ach on. Nam Pr LO: I can dscrib a similarity transformation,

More information

Midterm 2 - Solutions 1

Midterm 2 - Solutions 1 COS 26 Gnral Computr Scinc Spring 999 Midtrm 2 - Solutions. Writ a C function int count(char s[ ]) that taks as input a \ trminatd string and outputs th numbr of charactrs in th string (not including th

More information

CSE 272 Assignment 1

CSE 272 Assignment 1 CSE 7 Assignmnt 1 Kui-Chun Hsu Task 1: Comput th irradianc at A analytically (point light) For point light, first th nrgy rachd A was calculatd, thn th nrgy was rducd by a factor according to th angl btwn

More information

Shift. Reduce. Review: Shift-Reduce Parsing. Bottom-up parsing uses two actions: Bottom-Up Parsing II. ABC xyz ABCx yz. Lecture 8.

Shift. Reduce. Review: Shift-Reduce Parsing. Bottom-up parsing uses two actions: Bottom-Up Parsing II. ABC xyz ABCx yz. Lecture 8. Rviw: Shift-Rduc Parsing Bottom-up parsing uss two actions: Bottom-Up Parsing II Lctur 8 Shift ABC xyz ABCx yz Rduc Cbxy ijk CbA ijk Prof. Aikn CS 13 Lctur 8 1 Prof. Aikn CS 13 Lctur 8 2 Rcall: h Stack

More information

Examples from Section 7.1: Integration by Parts Page 1

Examples from Section 7.1: Integration by Parts Page 1 Examples from Section 7.: Integration by Parts Page Questions Example Determine x cos x dx. Example e θ cos θ dθ Example You may wonder why we do not add a constant at the point where we integrate for

More information

Learning Enhancement Team

Learning Enhancement Team Larning Enhanmnt Tam Modl Answrs: Intgration y Parts Ths ar th modl answrs for th worksht that has qstions on intgration y parts. Intgration y Parts stdy gid is sital for intgration y parts with a. d.

More information

On Some Maximum Area Problems I

On Some Maximum Area Problems I On Som Maximum Ara Problms I 1. Introdution Whn th lngths of th thr sids of a triangl ar givn as I 1, I and I 3, thn its ara A is uniquly dtrmind, and A=s(s-I 1 )(s-i )(s-i 3 ), whr sis th smi-primtr t{i

More information

Problem Set 1 (Due: Friday, Sept. 29, 2017)

Problem Set 1 (Due: Friday, Sept. 29, 2017) Elctrical and Computr Enginring Mmorial Univrsity of Nwfoundland ENGI 9876 - Advancd Data Ntworks Fall 2017 Problm St 1 (Du: Friday, Spt. 29, 2017) Qustion 1 Considr a communications path through a packt

More information

A Brief Summary of Draw Tools in MS Word with Examples! ( Page 1 )

A Brief Summary of Draw Tools in MS Word with Examples! ( Page 1 ) A Brif Summary of Draw Tools in MS Word with Exampls! ( Pag 1 ) Click Viw command at top of pag thn Click Toolbars thn Click Drawing! A chckmark appars in front of Drawing! A toolbar appars at bottom of

More information

The Network Layer: Routing Algorithms. The Network Layer: Routing & Addressing Outline

The Network Layer: Routing Algorithms. The Network Layer: Routing & Addressing Outline PS 6 Ntwork Programming Th Ntwork Layr: Routing lgorithms Michl Wigl partmnt of omputr Scinc lmson Univrsity mwigl@cs.clmson.du http://www.cs.clmson.du/~mwigl/courss/cpsc6 Th Ntwork Layr: Routing & ddrssing

More information

CPSC 826 Internetworking. The Network Layer: Routing & Addressing Outline. The Network Layer: Routing Algorithms. Routing Algorithms Taxonomy

CPSC 826 Internetworking. The Network Layer: Routing & Addressing Outline. The Network Layer: Routing Algorithms. Routing Algorithms Taxonomy PS Intrntworking Th Ntwork Layr: Routing & ddrssing Outlin Th Ntwork Layr: Routing lgorithms Michl Wigl partmnt of omputr Scinc lmson Univrsity mwigl@cs.clmson.du Novmbr, Ntwork layr functions Routr architctur

More information

Objectives. Two Ways to Implement Lists. Lists. Chapter 24 Implementing Lists, Stacks, Queues, and Priority Queues

Objectives. Two Ways to Implement Lists. Lists. Chapter 24 Implementing Lists, Stacks, Queues, and Priority Queues Chaptr 24 Implmnting Lists, Stacks, Quus, and Priority Quus CS2: Data Structurs and Algorithms Colorado Stat Univrsity Original slids by Danil Liang Modifid slids by Chris Wilcox Objctivs q To dsign common

More information

About Notes And Symbols

About Notes And Symbols About Nots And Symbols by Batric Wildr Contnts Sht 1 Sht 2 Sht 3 Sht 4 Sht 5 Sht 6 Sht 7 Sht 8 Sht 9 Sht 10 Sht 11 Sht 12 Sht 13 Sht 14 Sht 15 Sht 16 Sht 17 Sht 18 Sht 19 Sht 20 Sht 21 Sht 22 Sht 23 Sht

More information

MAT137 Calculus! Lecture 31

MAT137 Calculus! Lecture 31 MAT137 Calculus! Lecture 31 Today: Next: Integration Methods: Integration Methods: Trig. Functions (v. 9.10-9.12) Rational Functions Trig. Substitution (v. 9.13-9.15) (v. 9.16-9.17) Integration by Parts

More information

Greedy Algorithms. Interval Scheduling. Greedy Algorithm. Optimality. Greedy Algorithm (cntd) Greed is good. Greed is right. Greed works.

Greedy Algorithms. Interval Scheduling. Greedy Algorithm. Optimality. Greedy Algorithm (cntd) Greed is good. Greed is right. Greed works. Algorithm Grdy Algorithm 5- Grdy Algorithm Grd i good. Grd i right. Grd work. Wall Strt Data Structur and Algorithm Andri Bulatov Algorithm Grdy Algorithm 5- Algorithm Grdy Algorithm 5- Intrval Schduling

More information

EE 231 Fall EE 231 Homework 10 Due November 5, 2010

EE 231 Fall EE 231 Homework 10 Due November 5, 2010 EE 23 Fall 2 EE 23 Homwork Du Novmbr 5, 2. Dsign a synhronous squntial iruit whih gnrats th following squn. (Th squn should rpat itslf.) (a) Draw a stat transition diagram for th iruit. This is a systm

More information

Principles of Programming Languages Topic: Formal Languages II

Principles of Programming Languages Topic: Formal Languages II Principls of Programming Languags Topic: Formal Languags II CS 34,LS, LTM, BR: Formal Languags II Rviw A grammar can b ambiguous i.. mor than on pars tr for sam string of trminals in a PL w want to bas

More information

CS364B: Frontiers in Mechanism Design Lecture #10: Coverage Valuations and Convex Rounding

CS364B: Frontiers in Mechanism Design Lecture #10: Coverage Valuations and Convex Rounding CS364B: Frontirs in Mchanism Dsign Lctur #10: Covrag Valuations and Convx Rounding Tim Roughgardn Fbruary 5, 2014 1 Covrag Valuations Rcall th stting of submodular biddr valuations, introducd in Lctur

More information

Science One Math. Jan

Science One Math. Jan Science One Math Jan 24 2018 Announcements Midterm : February 13 th, 2018 Details on topics and list of practice problems to appear on course webpage soon. What integration techniques have we learned so

More information

Reimbursement Requests in WORKS

Reimbursement Requests in WORKS Rimbursmnt Rqusts in WORKS Important points about Rimbursmnts in Works Rimbursmnt Rqust is th procss by which UD mploys will b rimbursd for businss xpnss paid using prsonal funds. Rimbursmnt Rqust can

More information

Intersection-free Dual Contouring on Uniform Grids: An Approach Based on Convex/Concave Analysis

Intersection-free Dual Contouring on Uniform Grids: An Approach Based on Convex/Concave Analysis Intrsction-fr Dual Contouring on Uniform Grids: An Approach Basd on Convx/Concav Analysis Charli C. L. Wang Dpartmnt of Mchanical and Automation Enginring, Th Chins Univrsity of Hong Kong E-mail: cwang@ma.cuhk.du.hk

More information

TCP Congestion Control. Congestion Avoidance

TCP Congestion Control. Congestion Avoidance TCP Congstion Control TCP sourcs chang th snding rat by modifying th window siz: Window = min {Advrtisd window, Congstion Window} Rcivr Transmittr ( cwnd ) In othr words, snd at th rat of th slowst componnt:

More information

Workbook for Designing Distributed Control Applications using Rockwell Automation s HOLOBLOC Prototyping Software John Fischer and Thomas O.

Workbook for Designing Distributed Control Applications using Rockwell Automation s HOLOBLOC Prototyping Software John Fischer and Thomas O. Workbook for Dsigning Distributd Control Applications using Rockwll Automation s HOLOBLOC Prototyping Softwar John Fischr and Thomas O. Bouchr Working Papr No. 05-017 Introduction A nw paradigm for crating

More information

FLASHING CHRISTMAS TREE KIT

FLASHING CHRISTMAS TREE KIT R4 FLASHING CHRISTMAS TREE KIT 9 10 8 7 11 6 R3 12 T4 C4 5 T3 R5 R7 13 C3 C2 4 14 R1 T2 R6 3 OWNER S MANUAL T1 R8 15 2 C1 R2 1 16 Cat. No. 277-8001 CUSTOM MANUFACTURED FOR TANDY CORPORATION LTD ASSEMBLY

More information

Motivation. Synthetic OOD concepts and reuse Lecture 4: Separation of concerns. Problem. Solution. Deleting composites that share parts. Or is it?

Motivation. Synthetic OOD concepts and reuse Lecture 4: Separation of concerns. Problem. Solution. Deleting composites that share parts. Or is it? Synthtic OOD concpts and rus Lctur 4: Sparation of concrns Topics: Complx concrn: Mmory managmnt Exampl: Complx oprations on composit structurs Problm: Mmory laks Solution: Rfrnc counting Motivation Suppos

More information

Modeling Surfaces of Arbitrary Topology using Manifolds 1

Modeling Surfaces of Arbitrary Topology using Manifolds 1 Modling Surfacs of Arbitrary Topology using Manifolds 1 Cindy M. Grimm John F. Hughs cmg@cs.brown.du (401) 863-7693 jfh@cs.brown.du (401) 863-7638 Th Scinc and Tchnology Cntr for Computr Graphics and Scintific

More information

Summary: Semantic Analysis

Summary: Semantic Analysis Summary: Smantic Analysis Chck rrors not dtctd by lxical or syntax analysis Intrmdiat Cod Scop rrors: Variabls not dfind Multipl dclarations Typ rrors: Assignmnt of valus of diffrnt typs Invocation of

More information

Science One Math. Jan

Science One Math. Jan Science One Math Jan 21 2019 Today s Goal: Compute Trigonometric Integrals Apply the technique of substitution to compute trigonometric integrals of the form sin % x cos * x dx for both m > 1 and n > 1

More information

Register Allocation. Register Allocation

Register Allocation. Register Allocation Rgistr Allocation Jingk Li Portlan Stat Univrsity Jingk Li (Portlan Stat Univrsity) CS322 Rgistr Allocation 1 / 28 Rgistr Allocation Assign an unboun numbr of tmporaris to a fix numbr of rgistrs. Exampl:

More information

Internet Technology 3/21/2016

Internet Technology 3/21/2016 Intrnt Tchnolog //6 Roting algorithm goal st hop rotr = sorc rotr last hop rotr = dstination rotr rotr Intrnt Tchnolog 8. Roting sitch rotr LAN Pal Kranoski Rtgrs Unirsit Spring 6 LAN Roting algorithm:

More information

Different shells (e.g. bash, ksh, tcsh, ash, sh) => different commands/scripts

Different shells (e.g. bash, ksh, tcsh, ash, sh) => different commands/scripts Shll Programming Diffrnt hll (.g. bah, kh, tch, ah, h) => diffrnt command/cript Why a hll cript? impl way to tring togthr a bunch of UNIX-command cript ar uually fat to gt going portabl acro th whol UNIX

More information

Gernot Hoffmann Sphere Tessellation by Icosahedron Subdivision. Contents

Gernot Hoffmann Sphere Tessellation by Icosahedron Subdivision. Contents Grnot Hoffmann Sphr Tssllation by Icosahdron Subdivision Contnts 1. Vrtx Coordinats. Edg Subdivision 3 3. Triangl Subdivision 4 4. Edg lngths 5 5. Normal Vctors 6 6. Subdividd Icosahdrons 7 7. Txtur Mapping

More information

i e ai E ig e v / gh E la ES h E A X h ES va / A SX il E A X a S

i e ai E ig e v / gh E la ES h E A X h ES va / A SX il E A X a S isto C o C or Co r op ra p a py ag yr g ri g g gh ht S S S V V K r V K r M K v M r v M rn v MW n W S r W Sa r W K af r: W K f : a H a M r T H r M rn w T H r Mo ns w T i o S ww c ig on a w c g nd af ww

More information

The semantic WEB Roles of XML & RDF

The semantic WEB Roles of XML & RDF Th smantic WEB Rols of XML & RDF STEFAN DECKER AND SERGEY MELNIK FRANK VAN HARMELEN, DIETER FENSEL, AND MICHEL KLEIN JEEN BROEKSTRA MICHAEL ERDMANN IAN HORROCKS Prsntd by: Iniyai Thiruvalluvan CSCI586

More information

Interfacing the DP8420A 21A 22A to the AN-538

Interfacing the DP8420A 21A 22A to the AN-538 Intrfacing th DP8420A 21A 22A to th 68000 008 010 INTRODUCTION This application not xplains intrfacing th DP8420A 21A 22A DRAM controllr to th 68000 Thr diffrnt dsigns ar shown and xplaind It is assumd

More information

RFC Java Class Library (BC-FES-AIT)

RFC Java Class Library (BC-FES-AIT) RFC Java Class Library (BC-FES-AIT) HELP.BCFESDEG Rlas 4.6C SAP AG Copyright Copyright 2001 SAP AG. All Rcht vorbhaltn. Witrgab und Vrvilfältigung disr Publikation odr von Tiln daraus sind, zu wlchm Zwck

More information

Building a Scanner, Part I

Building a Scanner, Part I COMP 506 Ric Univrsity Spring 2018 Building a Scannr, Part I sourc cod IR Front End Optimizr Back End IR targt cod Copyright 2018, Kith D. Coopr & Linda Torczon, all rights rsrvd. Studnts nrolld in Comp

More information

Lesson Focus: Finding Equivalent Fractions

Lesson Focus: Finding Equivalent Fractions Lsson Plans: Wk of 1-26-15 M o n Bindrs: /Math;; complt on own, thn chck togthr Basic Fact Practic Topic #10 Lsson #5 Lsson Focus: Finding Equivalnt Fractions *Intractiv Larning/Guidd Practic-togthr in

More information

: Mesh Processing. Chapter 6

: Mesh Processing. Chapter 6 600.657: Msh Procssing Chaptr 6 Quad-Dominant Rmshing Goal: Gnrat a rmshing of th surfac that consists mostly of quads whos dgs align with th principal curvatur dirctions. [Marinov t al. 04] [Alliz t al.

More information

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Directed Graphs BOS SFO

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Directed Graphs BOS SFO Prsntation for us with th txtbook, Algorithm Dsign and Applications, by M. T. Goodrich and R. Tamassia, Wily, 2015 Dirctd Graphs BOS ORD JFK SFO LAX DFW MIA 2015 Goodrich and Tamassia Dirctd Graphs 1 Digraphs

More information

2 Unit Bridging Course Day 10

2 Unit Bridging Course Day 10 1 / 31 Unit Bridging Course Day 10 Circular Functions III The cosine function, identities and derivatives Clinton Boys / 31 The cosine function The cosine function, abbreviated to cos, is very similar

More information

Outline. Tasks for Exercise Six. Exercise Six Goals. Task One: Kinetic Energy Table. Nested for Loops. Laboratory VI Program Control Using Loops

Outline. Tasks for Exercise Six. Exercise Six Goals. Task One: Kinetic Energy Table. Nested for Loops. Laboratory VI Program Control Using Loops Ercis 6 -- Loopig March 9, 6 Laboratory VI Program Cotrol Usig Loops Larry Cartto Computr Scic 6 Computig i Egirig ad Scic Outli Ercis si goals Outli tasks for rcis si Itroduc ida of std loops ad tabl

More information

Forward and Inverse Kinematic Analysis of Robotic Manipulators

Forward and Inverse Kinematic Analysis of Robotic Manipulators Forward and Invrs Kinmatic Analysis of Robotic Manipulators Tarun Pratap Singh 1, Dr. P. Sursh 2, Dr. Swt Chandan 3 1 M.TECH Scholar, School Of Mchanical Enginring, GALGOTIAS UNIVERSITY, GREATER NOIDA,

More information

18.01 Single Variable Calculus Fall 2006

18.01 Single Variable Calculus Fall 2006 MIT OpenCourseWare http://ocw.mit.edu 18.01 Single Variable Calculus Fall 006 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Lecture 6: Trigonometric

More information

Changing Variables in Multiple Integrals

Changing Variables in Multiple Integrals Changing Variables in Multiple Integrals 3. Examples and comments; putting in limits. If we write the change of variable formula as (x, y) (8) f(x, y)dx dy = g(u, v) dudv, (u, v) where (x, y) x u x v (9)

More information

Mathematics 134 Calculus 2 With Fundamentals Exam 2 Answers/Solutions for Sample Questions March 2, 2018

Mathematics 134 Calculus 2 With Fundamentals Exam 2 Answers/Solutions for Sample Questions March 2, 2018 Sample Exam Questions Mathematics 1 Calculus 2 With Fundamentals Exam 2 Answers/Solutions for Sample Questions March 2, 218 Disclaimer: The actual exam questions may be organized differently and ask questions

More information

LAB1: DMVPN Theory. DMVPN Theory. Disclaimer. Pag e

LAB1: DMVPN Theory. DMVPN Theory. Disclaimer. Pag e LAB1: DMVPN Thory Disclaimr This Configuration Guid is dsignd to assist mmbrs to nhanc thir skills in rspctiv tchnology ara. Whil vry ffort has bn mad to nsur that all matrial is as complt and accurat

More information

Spectral sensitivity and color formats

Spectral sensitivity and color formats FirWir camras Spctral snsitivity and color formats At th "input" of a camra, w hav a CCD chip. It transforms photons into lctrons. Th spctral snsitivity of this transformation is an important charactristic

More information

Recorder Variables. Defining Variables

Recorder Variables. Defining Variables Rcordr Variabls Dfining Variabls Simpl Typs Complx Typs List of Rsrvd Words Using Variabls Stting Action Paramtrs Parsing Lists and Tabls Gtting Valu from Lists and Tabls Using Indxs with Lists Using Indxs

More information

Type & Media Page 1. January 2014 Libby Clarke

Type & Media Page 1. January 2014 Libby Clarke Nam: 1 In ordr to hlp you s your progrss at th nd of this ntir xrcis, you nd to provid som vidnc of your starting point. To start, draw th a on th lft into th box to th right, dpicting th sam siz and placmnt.

More information

Clustering Belief Functions using Extended Agglomerative Algorithm

Clustering Belief Functions using Extended Agglomerative Algorithm IJ Imag Graphics and Signal Procssing 0 - Publishd Onlin Fbruary 0 in MECS (http://wwwmcs-prssorg/ ing Blif Functions using Extndd Agglomrativ Algorithm Ying Png Postgraduat Collg Acadmy of Equipmnt Command

More information

Dual-mode Operation of the Finger-type Manipulator Based on Distributed Actuation Mechanism

Dual-mode Operation of the Finger-type Manipulator Based on Distributed Actuation Mechanism 11 th World Congrss on Structural and Multidisciplinary Optimisation 07 th -1 th, Jun 015, Sydny Australia Dual-mod Opration of th Fingr-typ Manipulator Basd on Distributd Actuation Mchanism Jong Ho Kim

More information

Modelling CoCoME with DisCComp

Modelling CoCoME with DisCComp Modlling CoCoME with DiCComp Dagtuhl Workhop, Sbatian Hrold Clauthal Univrity of Tchnology Dpartmnt of Informatic Softwar Sytm Enginring Chair of Prof. Dr. Andra Rauch Ovrviw Introduction Introduction

More information

WebAssign Lesson 3-2b Integration by Parts 2 (Homework)

WebAssign Lesson 3-2b Integration by Parts 2 (Homework) WebAssign Lesson 3-2b Integration by Parts 2 (Homework) Current Score : / 28 Due : Tuesday, July 15 2014 10:59 AM MDT Jaimos Skriletz Math 175, section 31, Summer 2 2014 Instructor: Jaimos Skriletz 1.

More information

Parametric Surfaces. Substitution

Parametric Surfaces. Substitution Calculus Lia Vas Parametric Surfaces. Substitution Recall that a curve in space is given by parametric equations as a function of single parameter t x = x(t) y = y(t) z = z(t). A curve is a one-dimensional

More information

I - Pre Board Examination

I - Pre Board Examination Cod No: S-080 () Total Pags: 06 KENDRIYA VIDYALAYA SANGATHAN,GUWHATI REGION I - Pr Board Examination - 04-5 Subjct Informatics Practics (Thory) Class - XII Tim: 3 hours Maximum Marks : 70 Instruction :

More information

MATH 19520/51 Class 15

MATH 19520/51 Class 15 MATH 19520/51 Class 15 Minh-Tam Trinh University of Chicago 2017-11-01 1 Change of variables in two dimensions. 2 Double integrals via change of variables. Change of Variables Slogan: An n-variable substitution

More information

Intersection-free Contouring on An Octree Grid

Intersection-free Contouring on An Octree Grid Intrsction-fr Contouring on An Octr Grid Tao Ju Washington Univrsity in St. Louis On Brookings Driv St. Louis, MO 0, USA taoju@cs.wustl.du Tushar Udshi Zyvx Corporation North Plano Road Richardson, Txas

More information

September 19, Some formal bits. 1.2 Lambda notation. 1.1 Type theory. Instead of writing the following... f : for all x, f(x) = Φ

September 19, Some formal bits. 1.2 Lambda notation. 1.1 Type theory. Instead of writing the following... f : for all x, f(x) = Φ Sptmbr 19, 2014 1 Som formal bits 1.2 Lambda notation Instad of writing th following... f : for all x, f(x) = Φ 1.1 Typ thory An xprssion s typ tlls you a numbr of things: W will writ th following: λx.φ

More information

Lightweight Polymorphic Effects

Lightweight Polymorphic Effects Lightwight Polymorphic Effcts Lukas Rytz, Martin Odrsky, and Philipp Hallr EPFL, Switzrland, {first.last}@pfl.ch Abstract. Typ-and-ffct systms ar a wll-studid approach for rasoning about th computational

More information

Managing Trust Relationships in Peer 2 Peer Systems

Managing Trust Relationships in Peer 2 Peer Systems Managing Trust Rlationships in Pr 2 Pr Systms R.S.SINJU PG STUDENT, DEPARTMENT OF COMPUTER SCIENCE, PONJESLY COLLEGE OF ENGINEERING NAGERCOIL, TAMILNADU, INDIA C.FELSY ASST.PROF, DEPARTMENT OF COMPUTER

More information

Lecture 19. Section 5.6 Indefinite Integrals Section 5.7 The u-substitution. Jiwen He. Department of Mathematics, University of Houston

Lecture 19. Section 5.6 Indefinite Integrals Section 5.7 The u-substitution. Jiwen He. Department of Mathematics, University of Houston Lecture 19 Section 5.6 Indefinite Integrals Section 5.7 The u-substitution Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu math.uh.edu/ jiwenhe/math1431 November 11, 2008

More information

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1 Advancd Computr Graphics CSE 63 [Spring 208], Lctur 7 Ravi Ramamoorthi http://www.cs.ucsd.du/~ravir To Do Assignmnt, Du Apr 27 Any last minut issus or difficultis? Starting Gomtry Procssing Assignmnt 2

More information

Non Fourier Encoding For Accelerated MRI. Arjun Arunachalam Assistant Professor Electrical engineering dept IIT-Bombay

Non Fourier Encoding For Accelerated MRI. Arjun Arunachalam Assistant Professor Electrical engineering dept IIT-Bombay Non Fourir Encoding For Acclratd MRI Arjun Arunachalam Assistant Profssor Elctrical nginring dpt IIT-Bombay Outlin of th Prsntation An introduction to Magntic Rsonanc Imaging (MRI Th nd for spd in MRI

More information

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE:

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE: SPCIFIC CRITRIA FOR TH GNRAL MOTORS GLOBAL TRADING PARTNR LABL TMPLAT: TH TMPLAT IDNTIFIS HOW AND WHR DATA IS TO B PLACD ON TH LABL WHN IT IS RQUIRD AS PART OF A GM BUSINSS RQUIRMNT FONT SIZS AR SPCIFID

More information

Ontology and Context. Isabel Cafezeiro Departamento de Ciência da Computação Universidade Federal Fluminense Niterói - RJ, Brazil

Ontology and Context. Isabel Cafezeiro Departamento de Ciência da Computação Universidade Federal Fluminense Niterói - RJ, Brazil Ontology and Contxt Isabl Cafziro Dpartamnto d Ciência da Computação Univrsidad Fdral Fluminns Nitrói - RJ, Brazil isabl@dcc.ic.uff.br dward Hrmann Hauslr, Alxandr Radmakr Dpartamnto d Informática Pontifícia

More information

Analysis of Influence AS Path Prepending to the Instability of BGP Routing Protocol.

Analysis of Influence AS Path Prepending to the Instability of BGP Routing Protocol. ISSN : 2355-9365 -Procding of Enginring : Vol.5, No.1 Mart 2018 Pag 1112 Analysis of Influnc AS Path Prpnding to th Instability of BGP Routing Protocol. Hirwandi Agusnam 1, Rndy Munadi 2, Istikmal 3 1,2,3,

More information

Ray Tracing. Ray Tracing. Ray Tracing. ray object. ray object = 0. Utah School of Computing Spring Computer Graphics CS5600

Ray Tracing. Ray Tracing. Ray Tracing. ray object. ray object = 0. Utah School of Computing Spring Computer Graphics CS5600 Utah School of omputing Spring 20 Wk Ra Tracing S5600 omputr Graphics From Rich Risnfl Spring 203 Ra Tracing lassical gomtric optics tchniqu Etrml vrsatil Historicall viw as pnsiv Goo for spcial ffcts

More information

Robust and Fault Tolerant Clock Synchronization Nikolaus Kerö, Oregano Systems Aneeq Mahmood, ZISS Thomas Kernen, Cisco Felix Ring, ZISS Tobias

Robust and Fault Tolerant Clock Synchronization Nikolaus Kerö, Oregano Systems Aneeq Mahmood, ZISS Thomas Kernen, Cisco Felix Ring, ZISS Tobias Robust and Fault Tolrant Clock Synchronization Nikolaus Krö, Organo Systms Anq Mahmood, ZISS Thomas Krnn, Cisco Flix Ring, ZISS Tobias Müllr, Organo Systms Thomas Biglr, ZISS Rational Common notion of

More information

A New Algorithm for Solving Shortest Path Problem on a Network with Imprecise Edge Weight

A New Algorithm for Solving Shortest Path Problem on a Network with Imprecise Edge Weight Availabl at http://pvamudu/aam Appl Appl Math ISSN: 193-9466 Vol 6, Issu (Dcmbr 011), pp 60 619 Applications and Applid Mathmatics: An Intrnational Journal (AAM) A Nw Algorithm for Solving Shortst Path

More information

KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION

KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION 03-4 Sub : Informatics Practics (065) Tim allowd : 3 hours Maximum Marks : 70 Instruction : (i) All qustions ar compulsory

More information

Multihop MIMO Relay Networks with ARQ

Multihop MIMO Relay Networks with ARQ Multihop MIMO Rlay Ntworks with ARQ Yao Xi Dniz Gündüz Andra Goldsmith Dpartmnt of Elctrical Enginring Stanford Univrsity Stanford CA Dpartmnt of Elctrical Enginring Princton Univrsity Princton NJ Email:

More information

Vignette to package samplingdatacrt

Vignette to package samplingdatacrt Vigntt to packag samplingdatacrt Diana Trutschl Contnts 1 Introduction 1 11 Objctiv 1 1 Diffrnt study typs 1 Multivariat normal distributd data for multilvl data 1 Fixd ffcts part Random part 9 3 Manual

More information

ME 582 Handout 7 2D FEM Code and Sample Input File

ME 582 Handout 7 2D FEM Code and Sample Input File METU Mchanical Enginring Dpartmnt ME 582 Finit Elmnt Analysis in Thrmofluids Spring 2018 (Dr. Srt) Handout 7 2D FEM Cod and a Sampl Input Fil ME 582 Handout 7 2D FEM Cod and Sampl Input Fil Download th

More information

and F is an antiderivative of f

and F is an antiderivative of f THE EVALUATION OF DEFINITE INTEGRALS Prepared by Ingrid Stewart, Ph.D., College of Southern Nevada Please Send Questions Comments to ingrid.stewart@csn.edu. Thank you! We have finally reached a point,

More information

To Do. Mesh Data Structures. Mesh Data Structures. Motivation. Outline. Advanced Computer Graphics (Fall 2010) Desirable Characteristics 1

To Do. Mesh Data Structures. Mesh Data Structures. Motivation. Outline. Advanced Computer Graphics (Fall 2010) Desirable Characteristics 1 Advancd Computr Graphics (Fall 200) CS 283, Lctur 5: Msh Data Structurs Ravi Ramamoorthi http://inst.cs.brkly.du/~cs283/fa0 To Do Assignmnt, Du Oct 7. Start rading and working on it now. Som parts you

More information

1. Trace the array for Bubble sort 34, 8, 64, 51, 32, 21. And fill in the following table

1. Trace the array for Bubble sort 34, 8, 64, 51, 32, 21. And fill in the following table 1. Trac th array for Bubbl sort 34, 8, 64, 51, 3, 1. And fill in th following tabl bubbl(intgr Array x, Intgr n) Stp 1: Intgr hold, j, pass; Stp : Boolan switchd = TRUE; Stp 3: for pass = 0 to (n - 1 &&

More information

Between Testing and Formal Verification

Between Testing and Formal Verification Btwn Tsting and Formal Vrification Jan Tobias Mühlbrg jantobias.muhlbrg@cs.kuluvn.b imc-distrint, KU Luvn, Clstijnnlaan 200A, B-3001 Blgium ScAppDv, Luvn, March 2017 1 /19 Jan Tobias Mühlbrg Btwn Tsting

More information

Lecture 39: Register Allocation. The Memory Hierarchy. The Register Allocation Problem. Managing the Memory Hierarchy

Lecture 39: Register Allocation. The Memory Hierarchy. The Register Allocation Problem. Managing the Memory Hierarchy Ltur 39: Rgistr Alloation [Aapt rom nots y R. Boik an G. Nula] Topis: Mmory Hirarhy Managmnt Rgistr Alloation: Rgistr intrrn graph Graph oloring huristis Spilling Cah Managmnt Th Mmory Hirarhy Computrs

More information

Graphing Calculator Activities

Graphing Calculator Activities Graphing Calculator Activitis Graphing Calculator Activitis Copyright 009, IPG Publishing IPG Publishing 86 Erin Bay Edn Prairi, innsota 47 phon: (6) 80-9090 www.iplaymathgams.com ISBN 978--948--6 IPG

More information

Metal-Oxide Varistors (MOVs) Radial Lead Varistors > UltraMOV TM 25S Varistor Series

Metal-Oxide Varistors (MOVs) Radial Lead Varistors > UltraMOV TM 25S Varistor Series UltraMOV 25S Varistor Sris RoHS Dscription Th UltraMOV 25S Varistor Sris is dsignd for applications rquiring high pak surg currnt ratings and high nrgy asorption capaility. UltraMOV varistors ar primarily

More information

Formal Foundation, Approach, and Smart Tool for Software Models Comparison

Formal Foundation, Approach, and Smart Tool for Software Models Comparison Formal Foundation, Approach, and Smart Tool for Softwar Modls Comparison Olna V. Chbanyuk, Abdl-Badh M. Salm Softwar Enginring Dpartmnt, National Aviation Univrsity, Kyiv, Ukrain Computr Scinc, Faculty

More information

S (surface mount) Issue date Manufacturer package code

S (surface mount) Issue date Manufacturer package code 1. Packag summary Tabl 1. Packag summary plastic, dual in-lin compatibl thrmal nhancd vry thin quad flat packag; 16 trminals; 0.5 mm pitch; 3.5 mm x 2.5 mm x 0.85 mm body 30 January 2017 Packag information

More information

Maxwell s unification: From Last Time. Energy of light. Modern Physics. Unusual experimental results. The photoelectric effect

Maxwell s unification: From Last Time. Energy of light. Modern Physics. Unusual experimental results. The photoelectric effect From Last Tim Enrgy and powr in an EM wav Maxwll s unification: 1873 Intimat connction btwn lctricity and magntism Exprimntally vrifid by Hlmholtz and othrs, 1888 Polarization of an EM wav: oscillation

More information

FSP Synthesis of an off-set five bar-slider mechanism with variable topology

FSP Synthesis of an off-set five bar-slider mechanism with variable topology FSP Synthsis of an off-st fiv bar-slidr mchanism with variabl topology Umsh. M. Daivagna 1*, Shrinivas. S. Balli 2 1 Dpartmnt of Mchanical Enginring, S.T.J.Institut of Tchnology, Ranbnnur, India 2 Dpt.

More information

the following minimization problem, termed as the rectilinear polygon cover problem: \Cover

the following minimization problem, termed as the rectilinear polygon cover problem: \Cover TWO GEOMETRIC OPTIMIZATION PROBLEMS BHASKAR DASGUPTA Dpartmnt of Computr Scinc Univrsity of Minnsota Minnapolis, MN 55455-0159 mail: dasgupta@cs.umn.du and VWANI ROYCHOWDHURY School of Elctrical Enginring

More information

EXTENSION OF RCC TOPOLOGICAL RELATIONS FOR 3D COMPLEX OBJECTS COMPONENTS EXTRACTED FROM 3D LIDAR POINT CLOUDS

EXTENSION OF RCC TOPOLOGICAL RELATIONS FOR 3D COMPLEX OBJECTS COMPONENTS EXTRACTED FROM 3D LIDAR POINT CLOUDS Th Intrnational rchivs of th Photogrammtry, mot Snsing and Spatial Information Scincs, Volum XLI-, 016 XXIII ISPS Congrss, 1 19 July 016, Pragu, Czch public EXTENSION OF CC TOPOLOGICL ELTIONS FO D COMPLEX

More information

TRIANGULATION OF NURBS SURFACES. Jamshid Samareh-Abolhassani. 1 Abstract

TRIANGULATION OF NURBS SURFACES. Jamshid Samareh-Abolhassani. 1 Abstract TRIANGULATION OF NURBS SURFACES Jamshid Samarh-Abolhassani 1 Abstract A tchniqu is prsntd for triangulation of NURBS surfacs. This tchniqu is built upon an advancing front tchniqu combind with grid point

More information

Paper Template and Style Guide for the Vapor Intrusion, Remediation, and Site Closure Conference

Paper Template and Style Guide for the Vapor Intrusion, Remediation, and Site Closure Conference Papr Tmplat and Styl Guid for th Vapor Intrusion, Rmdiation, and Sit Closur Confrnc This Tmplat and Styl Guid dtail th documnt formatting standards and xpctd contnt for a full lngth papr manuscript. Your

More information

A positional container ("pcontainer" for short) is a generic container that is organized by position, which means

A positional container (pcontainer for short) is a generic container that is organized by position, which means Chaptr: Gnric Positional Containrs and Doul Endd Quus Gnric Positional Containrs A positional containr is a gnric containr that stors lmnts y position at th discrtion of a clint. For xampl, a vctor stors

More information

Update-Aware Accurate XML Element Retrieval

Update-Aware Accurate XML Element Retrieval Updat-Awar Accurat XML Elmnt Rtrival Atsushi Kyaki, Jun Miyazaki Graduat School of Information Scinc Nara Institut of Scinc and Tchnology 8916-5 Takayama, Ikoma Nara 630-0192, Japan {atsushi-k, miyazaki}@is.naist.jp

More information

How to fix your 260Z or 280Z clock.

How to fix your 260Z or 280Z clock. Sujt Fixing th Kanto Siki lok Author E. Bttio How to fix your 260Z or 280Z lok. I first wrot this up aout two yars ago. This is th sond vrsion of this produr. It is not vry muh diffrnt to my first ffort

More information

Terrain Mapping and Analysis

Terrain Mapping and Analysis Trrain Mapping and Analysis Data for Trrain Mapping and Analysis Digital Trrain Modl (DEM) DEM rprsnts an array of lvation points. Th quality of DEM influncs th accuracy of trrain masurs such as slop and

More information

Evolutionary Clustering and Analysis of Bibliographic Networks

Evolutionary Clustering and Analysis of Bibliographic Networks Evolutionary Clustring and Analysis of Bibliographic Ntworks Manish Gupta Univrsity of Illinois at Urbana-Champaign gupta58@illinois.du Charu C. Aggarwal IBM T. J. Watson Rsarch Cntr charu@us.ibm.com Jiawi

More information

Fuzzy Intersection and Difference Model for Topological Relations

Fuzzy Intersection and Difference Model for Topological Relations IFS-EUSFLT 009 Fuzzy Intrsction and Diffrnc Modl for Topological Rlations hd LOODY Flornc SEDES Jordi INGLD 3 Univrsité Paul Sabatir (UPS) Toulous, 8 Rout d Narbonn, F-306-CEDEX 9, Franc Institut d Rchrchn

More information

High-Frequency RFID Tags: An Analytical and Numerical Approach for Determining the Induced Currents and Scattered Fields

High-Frequency RFID Tags: An Analytical and Numerical Approach for Determining the Induced Currents and Scattered Fields High-Frquncy RFID Tags: An Analytical and Numrical Approach for Dtrmining th Inducd Currnts and Scattrd Filds Bnjamin D. Braatn Elctrical and Computr Enginring North Dakota Stat Univrsity Fargo, North

More information